Kinase signaling is a major mechanism driving many cancers. While many inhibitors have been developed and are employed in the clinic, resistance due to crosstalk and pathway reprogramming is an emerging problem. High-throughput assays to detect multiple pathway kinases simultaneously could better model these complex relationships and enable drug development to combat this type of resistance.
The discovery that specific molecular targets in cancer can be controlled with kinase inhibitor drugs revolutionized modern chemotherapy and created a new paradigm for drug development and treatment. Based on its blockbuster success, the kinase inhibitor drug imatinib (IM) (also known as Gleevec™), has become the first-line therapy for chronic myeloid leukemia (CML). IM targets the oncogenic kinase Bcr-Abl, the fusion protein resulting from the translocation of chromosomes 9 and 22 (known as the Philadelphia chromosome, the hallmark of CML), and initially induces remission in nearly all CML patients. A significant proportion of these patients (approximately 60-70%) maintain remission for ≥5 years (remarkable for a disease that previously had estimated 5-year survival rates of less than 50%).
Unfortunately, these kinase inhibitor ‘magic bullets’ are not comprehensively curative. Approximately 10% of CML patients fail to respond at all, even if they are Bcr-Abl positive, and approximately 20-30% of those who initially do respond quickly develop resistance to IM (within 1-5 years). The pharmacodynamic response of a given individual (i.e. the effect of the inhibitor on the kinase in their tumor cells) varies, for example due to pharmacokinetic differences and expression of cellular transporters. Studies have shown that achieving at least 10-fold reduction in the BCR-ABL/ABL1 transcript ratio is the strongest predictor of long-term success on kinase inhibitors in CML (as opposed to the previous benchmark of “major molecular response,” MMR, which is a 103-fold reduction in this ratio), however, mRNA levels are not a direct pharmacodynamic effect, they are a result of cell death which is a downstream outcome of the direct action of the drug on its target. Evidence suggests that a >50% reduction in Bcr-Abl substrate phosphorylation (a direct effect) in a patient's tumor cells within the first 28 days of treatment is associated with achieving that 10-fold reduction in transcript ratios. This means that just by looking at the effect of the drug on its target and related pathways, physicians would have the opportunity to change treatment plans within the first month if efficacy was not achieved, but currently, this direct pharmacodynamic response is not measured in the clinic.
The complexity of the signaling pathways can also be a confounding factor. Since other kinases (such as the JAK2 and Src-family pathways) can also contribute to CML, some drugs may hit one target but miss other crucial drivers of disease. This is important in CML resistance and relapse, but especially a problem with other leukemias, e.g. Ph+ acute myelogenous (AML) and acute lymphocytic (ALL) leukemias, which frequently do not respond to kinase inhibitors for reasons that are not well understood. In chronic lymphocytic leukemia (CLL), the mobilized, circulating tumor cells tend to be drug sensitive while those sequestered in lymphatic tissue are resistant (possibly due to competing survival signals maintained by the microenvironment). As a result, despite being a relatively low (9th) in the list of cancer incidence in the US and despite the success of IM, leukemias still represent the 6th most deadly class of cancer. Clearly there is still a need for better management of these diseases.
The heterogeneity of cancer signaling (including differences between individuals and within a given individual's disease) is a major challenge to drug discovery and dosage for kinase inhibitors. Primary cancers are vastly heterogeneous, with an array of genetic and proteomic characteristics. Therefore, it is not surprising that many kinase inhibitor drugs fail clinical trials; if every patient has a novel tumor population phenotype (that furthermore differs from the model systems used to develop the drug), predicting response de novo is next to impossible, and success in some patients is diluted in statistical analysis by lack of response in others. “Personalized medicine” has emerged to address this, however, applications of this concept in the clinic have been limited to the genetic level. Many critical features of kinase signaling are regulated at the post-translational level (e.g. modifications of kinase or substrate, subcellular scaffolding, and localized sequestration), for which genetic techniques are not informative. In addition, drug discovery does not usually incorporate pre-clinical examination of heterogeneity at the post-translational level. Though there are some methods that can approach this (such as immunostaining and flow cytometry profiling of patient tumor cells), they are generally low-throughput and unsatisfactory for highly multiplexed applications.
Kinase inhibitors represent $12 billion of today's oncology drug market (˜19% of the total cancer therapeutics market) and their share is projected to keep growing (reaching upwards of $17 billion by 2017). Imatinib will soon be off-patent and will become widely available as a generic (at approximately 10-fold lower cost), so it will likely continue to be the primary first-line treatment for CML, however, competitor next-generation inhibitors are now being pushed to replace imatinib. These more expensive inhibitors may or may not be better for a given patient, and doctors will need pharmacodynamic information to make the right decisions, avoiding excessive costliness while making sure a drug is working for a patient. Accordingly, methods to monitor, manage and optimize kinase inhibitor choice will be crucial to controlling costs and improving patient outcomes. The future of inhibitor treatment management, as well as pre-clinical and clinical inhibitor development, will require expansion of the toolbox to build integrated pictures of signaling dynamics in cultured and primary cells.
Since it is routinely used for metabolite analysis, many clinical labs have targeted MS instrumentation available. Cell-based kinase profiling technology could transform inhibitor treatment at all stages: drug discovery, pre-clinical and clinical development, and patient care. It could aid target validation by providing on- and off-target information. It could improve the analysis of meaningful outcomes in pre-clinical and clinical trials, and it could enable specialization of treatment for individual cancer patients, allowing ‘real-time’ dose adjustment to reach a given patient's optimal therapeutic window for kinase inhibition.
Currently, the most informative diagnostic markers (BCR-ABL/ABL1 transcript ratios) are first assessed at three months after initiating imatinib or other kinase inhibitor treatment. The monetary cost of three months of unsuccessful imatinib treatment approaches $20,000 per patient, with approximately 4800 new cases of CML per year and 3-month failure rate of ˜10%. This translates to nearly $100 million in costs, skyrocketing even more when the rate of relapse within 1-5 years is taken into account. More importantly, this wasted time represents lost opportunities to improve a patient's treatment and potentially position them for long-term success. Strategies that address this gap in the standard of care for CML could transform kinase inhibitor treatment, and serve as a model system for introducing pharmacodynamics into personalized medicine in other cancers. Based on the current evidence, these strategies will require cell-based measurements of kinase activity in a patient's own tumor cells. Furthermore, focusing on inhibitor combinations for more than one kinase at a time will facilitating characterization of key on- and off-target inhibitory effects of multiple compounds in the same cell, revealing early stages of resistance, and enabling timely intervention.
Multiplexed kinase activity detection has remained a challenge in the field, with only a few examples of successful implementation. Existing examples of this strategy typically use dual antibody labelling, with one antibody tagged with a small molecule fluorophore for emission and the other labelled with a chelated lanthanide for sensitization. Alternatively, existing examples tag the substrate with a fluorophore (either small molecule or protein) and use a phosphospecific antibody labelled with a chelated lanthanide for sensitization. In either case, highly specific antibodies are required (but may not be available for the desired analytes) to enable multiplexing.
Genetically-encoded FRET-based sensor proteins are the current state-of-the-art for fluorescence detection of phosphorylation dynamics in live cells, and have led to significant advances in analyzing intracellular kinase activity (Gao, X.; Zhang, J., Chembiochem 2010, 11 (2), 147-51; and Ni, Q.; Zhang, J., Advances in biochemical engineering/biotechnology 2010, 119, 79-97). However, because these sensors require expression by the cell, and there are only a certain number of genetically-encodable FRET pairs currently available, it is not practical to analyze more than 1-2 kinase targets at a time using this technique (Grant, D. M., et al., Biophysical journal 2008, 95 (10), L69-71; and Piljic, A.; Schultz, C., ACS Chem Biol 2008, 3 (3), 156-60). Synthetic and FRET-based peptide kinase substrates (Lawrence, D. S.; Wang, Q., Chembiochem 2007, 8 (4), 373-8; Sharma, V., et al., J Am Chem Soc 2007, 129 (10), 2742-3; Wang, Q., et al., ACS Chem Biol 2010, 5 (9), 887-95; Shults, M. D., et al., Nature Methods 2005, 2 (4), 277-283; Lukovic, E., et al., J Am Chem Soc 2008, 130 (38), 12821-7; Stains, C. I., et al., Chem Biol 2012, 19 (2), 210-7; Ghadiali, J. E, et al., ACS nano 2010, 4 (8), 4915-9; and Lowe, S. B, et al., ACS nano 2012, 6 (1), 851-7) could potentially be more multiplex-compatible (based on the options for synthetic fluorophores), however, while they have been successful in cell lysates, they have had limited application to intact cells, and may be limited by their intrinsic signal to noise (which is usually on the order of 3-5-fold signal enhancement upon phosphorylation) (Yeh, R. H, et al., J Biol Chem 2002, 277 (13), 11527-32; and Dai, Z, et al., Chem Biol 2007, 14 (11), 1254-60).
Proteomic assays (e.g. KAYAK, Kubota, K, et al., Nat Biotechnol 2009, 27 (10), 933-40; and Kunz, R. C, et al., Analytical Chemistry 2012, 84 (14), 6233-6239) are excellent for in vitro multiplexing, but since they are performed with cell lysates, cellular context and any associated regulation are lost. Also, concentrations of drug and enzyme interacting inside the cell are not the same as the concentrations of these components in lysate, thus, the relative “dose” of inhibitor experienced by the enzyme is very different post-lysis. Furthermore, lysate-based assays don't take into account drug uptake differences (through e.g. the OCT-1 transporter (White, D. L, et al., J Clin Oncol 2010) or efflux (through multidrug resistance pumps). All of these can confound the interpretation of drug pharmacology when attempting to assess the degree of kinase inhibition in a patient's tumor cells. Synthetic substrates can be tagged for cell uptake using cell penetrating peptides and other cell membrane permeable moieties, and it has been shown that they can be phosphorylated in a kinase-specific manner (Placzek, E. A, et al., Anal Biochem 2010, 397 (1), 73-8; Lipchik, A. M, et al., Biochemistry 2012, 51 (38), 7515-7524; Tang, J, et al., Chembiochem 2012, 13 (5), 665-73; Meredith, G. D, et al., Nat Biotechnol 2000, 18 (3), 309-12; Soughayer, J. S, et al., Biochemistry 2004, 43 (26), 8528-8540; and Proctor, A, et al., Anal Chem 2012, 84 (16), 7195-202). However, the previous detection methods employed with these sensors have required extensive handling with unique instrumentation, antibody-based detection, and/or specialized electrophoresis, hampering their widespread application to multiplexed signaling pathways.
Recent work has established multiplexed flow cytometry techniques using tagged antibodies against endogenous kinase substrate phosphorylation sites to map out signaling networks in cell models and primary cells from patients at the single-cell level (Irish, J. M., et al., Nat Rev Cancer 2006, 6 (2), 146-55; and Irish, J. M, et al., Proc Natl Acad Sci USA 2010, 107 (29), 12747-54). This work has defined many key parameters for how to handle and stimulate primary cells to get realistic signaling behavior. Recent technology development, particularly using inductively-coupled plasma mass spectrometry (ICP-MS) and metal ion-tagged antibodies (Bendall, S. C., et al., Science 2011, 332 (6030), 687-96) has expanded the multiplexability of these techniques to >20 sites in a single experiment. While this strategy breaks several boundaries in the field and produces highly biologically relevant data, it is dependent on immunochemistry for antibody recognition of the endogenous sites. Immunochemistry is limited by the need to produce specific antibodies, with varying sensitivity from antibody to antibody, significant background binding unrelated to the epitope of interest, and the requirement for pre-knowledge of meaningful substrate sites. Moreover, any method that detects endogenous phosphoproteins/peptides gives a snapshot of the cell's current steady state, from which transient or time-dependent changes in activity are difficult to dissect.
Accordingly, there is currently a need for new detection strategies that offer sensitive and specific detection of multiple kinase activities that can enhance the depth of information obtained in a screening assay, monitor more than one signal simultaneously and mimic reconstitution of the relevant pathways, without relying on the availability or development of antibodies for detection.